About me
I am Ritten, an AI-researcher with a diverse skill set. My drive is to find solutions to complex problems using custom build AI applications, with a special interest in the agricultural and biology domains.
During my Masters degree in Artificial Intelligence at the University of Groningen, I encountered subjects such as machine learning, logic, knowledge systems, cognitive psychology, neuro-ergonomics, microbiology and atmospheric modeling.
- Full Name : H.M. Roothaert
- Date of Birth: 07-02-1998
- Website : https://ritten11.github.io
- Email : h.m.roothaert@gmail.com
Curious
Curiosity is what motivates my to explore new fields of research and broaden my horizon. Seeing how other people solved the problems they encountered is a major source for my own inspiration.
Unconventional
Just because something has become the status-quo, does not mean there is no room for improvement. The most interesting ideas come from least expected places.
Dedicated
Rome was not build in a day, and neither can major problems be solved with minimal effort. Going the extra mile is a requirement for delivering a well developed and tested product.
Programming skills
My preferred programming languages are Python and Java, but am also acquainted with R, Lisp and C.
Languages
I can speak both English and Dutch fluently, and understand German and Norwegian.
Personality
Personality traits I would bring to a professional team are: team-oriented competitiveness, unconventional thinking and the ability to quickly understand new concepts.
Notable accomplishments
I’m always eager to learn about fields outside of his main expertise and look for ways on how to implement my skill set to these fields. This has been demonstrated by various projects, one of which being my contribution to the iGEM competition. The iGEM competition is a competition where teams from across the world aim to use molecular microbiology to solve real-world problems. Without much background knowledge about the field of microbiology, I have managed to build an ML-model which was eventually nominated for ‘best model’ award in the overgraduate category. Other contributions to the team were human practice work and being the financial manager of the team. As icing on the cake, we even won the ‘best environmental project’ award, also within the overgraduate category!
Furthermore, I have finished my Master’s project in a field in which I had no prior knowledge; atmospheric inversions. The term atmospheric inversions is used to classify a wide range of techniques used to deduce a prior atmospheric state based on observations. What this state looks like depend on the domain of application. For my Master’s project, this state represented the biases within CO2 surface flux models. Using my research, a better forecast model of these biases has been created, increasing our confidence in the global CO2 surface flux landscape. The final grade for this project was an 8.5, with a publication still pending.